{"id":"W3213061076","doi":"10.1016/j.mran.2021.100186","title":"Microbial risk assessment and mitigation options for wastewater treatment in Arctic Canada","year":2021,"lang":"en","type":"article","venue":"Microbial Risk Analysis","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; Dalhousie University","funders":"Nasivvik Centre for Inuit Health and Changing Environments; Government of Nunavut","keywords":"Environmental science; Wastewater; Effluent; Sewage treatment; Arctic; Risk assessment; Recreation; Environmental protection; Risk analysis (engineering); Environmental engineering; Ecology; Business; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004354454,0.0001825653,0.0005354948,0.0001741855,0.002720895,0.00001837989,0.00005863706,0.0001378775,0.0003230741],"category_scores_gemma":[0.00007948811,0.0001617098,0.0001819864,0.0004518706,0.00003463135,0.00003990249,0.00009100768,0.0002542241,0.000009728009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002304484,"about_ca_system_score_gemma":0.001454588,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8734021,"about_ca_topic_score_gemma":0.9984713,"domain_scores_codex":[0.9976823,0.000557732,0.0005331429,0.0004120753,0.00007129652,0.000743467],"domain_scores_gemma":[0.9988133,0.0003515096,0.0002462719,0.0002378232,0.0002663654,0.00008472538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005939832,0.0002300442,0.9771508,0.0000856998,0.00240684,0.00002391679,0.01086772,0.001965843,0.004100623,0.00009591575,0.002370053,0.0006431328],"study_design_scores_gemma":[0.007039593,0.00036856,0.8644323,0.00007657853,0.01083325,0.000007461332,0.04615826,0.004119287,0.001480344,0.0003602004,0.06426635,0.0008577696],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956784,0.0002225552,0.0003277317,0.001643244,0.000359385,0.000739886,0.0009123875,0.00001158686,0.0001048495],"genre_scores_gemma":[0.9932917,0.001402233,0.00258665,0.0002787893,0.0001671997,0.000271097,0.0005777252,0.00001740743,0.001407151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1250692,"threshold_uncertainty_score":0.9985774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01527638729345003,"score_gpt":0.3328232756970806,"score_spread":0.3175468884036305,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}